Urinary Biomarkers and Kidney Injury in VA NEPHRON-D: Phenotyping Acute Kidney Injury in Clinical Trials.

RATIONALE & OBJECTIVE: Urinary biomarkers of injury, inflammation, and repair may help phenotype acute kidney injury (AKI) observed in clinical trials. We evaluated the differences in biomarkers between participants randomized to monotherapy or to combination renin-angiotensin-aldosterone system (RAAS) blockade in VA NEPHRON-D, where an increased proportion of observed AKI was acknowledged in the combination arm. STUDY DESIGN: Longitudinal analysis. SETTING & PARTICIPANTS: A substudy of the VA NEPHRON-D trial. PREDICTOR: Primary exposure was the treatment arm (combination [RAAS inhibitor] vs monotherapy). AKI is used as a stratifying variable. OUTCOME: Urinary biomarkers, including albumin, EGF (epidermal growth factor), MCP-1 (monocyte chemoattractant protein-1), YKL-40 (chitinase 3-like protein 1), and KIM-1 (kidney injury molecule-1). ANALYTICAL APPROACH: Biomarkers measured at baseline and at 12 months in trial participants were compared between treatment groups and by AKI. AKI events occurring during hospitalization were predefined safety end points in the original trial. The results were included in a meta-analysis with other large chronic kidney disease trials to assess global trends in biomarker changes. RESULTS: In 707 participants followed for a median of 2.2 years, AKI incidence was higher in the combination (20.7%) versus the monotherapy group (12.7%; relative risk [RR], 1.64 [95% CI, 1.16-2.30]). Compared with the monotherapy arm, in the combination arm the urine biomarkers at 12 months were either unchanged (MCP-1: RR, -3% [95% CI, -13% to 9%], Padj=0.8; KIM-1: RR, -10% [95% CI, -20% to 1%], Padj=0.2; EGF, RR-7% [95% CI, -12% to-1%], Padj=0.08) or lower (albuminuria: RR, -24% [95% CI, -37% to-8%], Padj=0.02; YKL: RR, -40% to-44% [95% CI, -58% to-25%], Padj<0.001). Pooled meta-analysis demonstrated reduced albuminuria in the intervention arm across 3 trials and similar trajectories in other biomarkers. LIMITATIONS: Biomarker measurement was limited to 2 time points independent of AKI events. CONCLUSIONS: Despite the increased risk of serum creatinine-defined AKI, combination RAAS inhibitor therapy was associated with unchanged or decreased urinary biomarkers at 12 months. This suggests a possible role for kidney biomarkers to further characterize kidney injury in clinical trials. PLAIN-LANGUAGE SUMMARY: The VA NEPHRON-D trial investigated inhibition of the renin-angiotensin-aldosterone system (RAAS) hormonal axis on kidney outcomes in a large population of diabetic chronic kidney disease patients. The trial was stopped early due to increased events of serum creatinine-defined acute kidney injury in the combination therapy arm. Urine biomarkers can serve as an adjunct to serum creatinine in identifying kidney injury. We found that urinary biomarkers in the combination therapy group were not associated with a pattern of harm and damage to the kidney, despite the increased number of kidney injury events in that group. This suggests that serum creatinine alone may be insufficient for defining kidney injury and supports further exploration of how other biomarkers might improve identification of kidney injury in clinical trials.

Urinary Plasminogen as a Marker of Disease Progression in Human Glomerular Disease.

RATIONALE & OBJECTIVE: Glomerular disorders have a highly variable clinical course, and biomarkers that reflect the molecular mechanisms underlying their progression are needed. Based on our previous work identifying plasminogen as a direct cause of podocyte injury, we designed this study to test the association between urine plasmin(ogen) (ie, plasmin and its precursor plasminogen) and end-stage kidney disease (ESKD). STUDY DESIGN: Multicenter cohort study. SETTING & PARTICIPANTS: 1,010 patients enrolled in the CureGN Cohort with biopsy-proven glomerular disease (focal segmental glomerulosclerosis, membranous nephropathy, and immunoglobulin A nephropathy). PREDICTORS: The main predictor was urine plasmin(ogen) at baseline. Levels were measured by an electrochemiluminescent immunoassay developed de novo. Traditional clinical and analytical characteristics were used for adjustment. The ratio of urine plasmin(ogen)/expected plasmin(ogen) was evaluated as a predictor in a separate model. OUTCOME: Progression to ESKD. ANALYTICAL APPROACH: Cox regression was used to examine the association between urinary plasmin(ogen) and time to ESKD. Urinary markers were log2 transformed to approximate normal distribution and normalized to urinary creatinine (Log2uPlasminogen/cr, Log2 urinary protein/cr [UPCR]). Expected plasmin(ogen) was calculated by multiple linear regression. RESULTS: Adjusted Log2uPlasminogen/cr was significantly associated with ESKD (HR per doubling Log2 uPlasminogen/cr 1.31 [95% CI, 1.22-1.40], P<0.001). Comparison of the predictive performance of the models including Log2 uPlasminogen/cr, Log2 UPCR, or both markers showed the plasmin(ogen) model superiority. The ratio of measured/expected urine plasmin(ogen) was independently associated with ESKD: HR, 0.41 (95% CI, 0.22-0.77) if ratio<0.8 and HR 2.42 (95% CI, 1.54-3.78) if ratio>1.1 (compared with ratio between 0.8 and 1.1). LIMITATIONS: Single plasmin(ogen) determination does not allow for the study of changes over time. The use of a cohort of mostly white patients and the restriction to patients with 3 glomerular disorders limits the external validity of our analysis. CONCLUSIONS: Urinary plasmin(ogen) and the ratio of measured/expected plasmin(ogen) are independently associated with ESKD in a cohort of patients with glomerular disease. Taken together with our previous experimental findings, urinary plasmin(ogen) could be a useful biomarker in prognostic decision making and a target for the development of novel therapies in patients with proteinuria and glomerular disease. PLAIN-LANGUAGE SUMMARY: Glomerular diseases are an important cause of morbidity and mortality in patients of all ages. Knowing the individual risk of progression to dialysis or transplantation would help to plan the follow-up and treatment of these patients. Our work studies the usefulness of urinary plasminogen as a marker of progression in this context, since previous studies indicate that plasminogen may be involved in the mechanisms responsible for the progression of these disorders. Our work in a sample of 1,010 patients with glomerular disease demonstrates that urinary plasminogen (as well as the ratio of measured to expected plasminogen) is associated with the risk of progression to end-stage kidney disease. Urine plasminogen exhibited good performance and, if further validated, could enable risk stratification for timely interventions in patients with proteinuria and glomerular disease.

The ASSESS-AKI Study found urinary epidermal growth factor is associated with reduced risk of major adverse kidney events.

Biomarkers of tubular function such as epidermal growth factor (EGF) may improve prognostication of participants at highest risk for chronic kidney disease (CKD) after hospitalization. To examine this, we measured urinary EGF (uEGF) from samples collected in the Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study, a multi-center, prospective, observational cohort of hospitalized participants with and without AKI. Cox proportional hazards regression was used to investigate the association of uEGF/Cr at hospitalization, three months post-discharge, and the change between these time points with major adverse kidney events (MAKE): CKD incidence, progression, or development of kidney failure. Clinical findings were paired with mechanistic studies comparing relative Egf expression in mouse models of kidney atrophy or repair after ischemia-reperfusion injury. MAKE was observed in 20% of 1,509 participants over 4.3 years of follow-up. Each 2-fold higher level of uEGF/Cr at three months was associated with decreased risk of MAKE (adjusted hazards ratio 0.46, 95% confidence interval: 0.39-0.55). Participants with the highest increase in uEGF/Cr from hospitalization to three-month follow-up had a lower risk of MAKE (adjusted hazards ratio 0.52; 95% confidence interval: 0.36-0.74) compared to those with the least change in uEGF/Cr. A model using uEGF/Cr at three months combined with clinical variables yielded moderate discrimination for MAKE (area under the curve 0.73; 95% confidence interval: 0.69-0.77) and strong discrimination for kidney failure at four years (area under the curve 0.96; 95% confidence interval: 0.92-1.00). Accelerated restoration of Egf expression in mice was seen in the model of adaptive repair after injury, compared to a model of progressive atrophy. Thus, urinary EGF/Cr may be a biomarker of distal tubular health, with higher concentrations and increased uEGF/Cr post-discharge independently associated with reduced risk of MAKE in hospitalized patients.

Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19.

RATIONALE & OBJECTIVE: Patients hospitalized with COVID-19 are at increased risk for major adverse kidney events (MAKE). We sought to identify plasma biomarkers predictive of MAKE in patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: A total of 576 patients hospitalized with COVID-19 between March 2020 and January 2021 across 3 academic medical centers. EXPOSURE: Twenty-six plasma biomarkers of injury, inflammation, and repair from first available blood samples collected during hospitalization. OUTCOME: MAKE, defined as KDIGO stage 3 acute kidney injury (AKI), dialysis-requiring AKI, or mortality up to 60 days. ANALYTICAL APPROACH: Cox proportional hazards regression to associate biomarker level with MAKE. We additionally applied the least absolute shrinkage and selection operator (LASSO) and random forest regression for prediction modeling and estimated model discrimination with time-varying C index. RESULTS: The median length of stay for COVID-19 hospitalization was 9 (IQR, 5-16) days. In total, 95 patients (16%) experienced MAKE. Each 1 SD increase in soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 was significantly associated with an increased risk of MAKE (adjusted HR [AHR], 2.30 [95% CI, 1.86-2.85], and AHR, 2.26 [95% CI, 1.73-2.95], respectively). The C index of sTNFR1 alone was 0.80 (95% CI, 0.78-0.84), and the C index of sTNFR2 was 0.81 (95% CI, 0.77-0.84). LASSO and random forest regression modeling using all biomarkers yielded C indexes of 0.86 (95% CI, 0.83-0.89) and 0.84 (95% CI, 0.78-0.91), respectively. LIMITATIONS: No control group of hospitalized patients without COVID-19. CONCLUSIONS: We found that sTNFR1 and sTNFR2 are independently associated with MAKE in patients hospitalized with COVID-19 and can both also serve as predictors for adverse kidney outcomes. PLAIN-LANGUAGE SUMMARY: Patients hospitalized with COVID-19 are at increased risk for long-term adverse health outcomes, but not all patients suffer long-term kidney dysfunction. Identification of patients with COVID-19 who are at high risk for adverse kidney events may have important implications in terms of nephrology follow-up and patient counseling. In this study, we found that the plasma biomarkers soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 measured in hospitalized patients with COVID-19 were associated with a greater risk of adverse kidney outcomes. Along with clinical variables previously shown to predict adverse kidney events in patients with COVID-19, both sTNFR1 and sTNFR2 are also strong predictors of adverse kidney outcomes.

Plasma Soluble Tumor Necrosis Factor Receptor Concentrations and Clinical Events After Hospitalization: Findings From the ASSESS-AKI and ARID Studies.

RATIONALE & OBJECTIVE: The role of plasma soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 in the prognosis of clinical events after hospitalization with or without acute kidney injury (AKI) is unknown. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: Hospital survivors from the ASSESS-AKI (Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury) and ARID (AKI Risk in Derby) studies with and without AKI during the index hospitalization who had baseline serum samples for biomarker measurements. PREDICTORS: We measured sTNFR1 and sTNFR2 from plasma samples obtained 3 months after discharge. OUTCOMES: The associations of biomarkers with longitudinal kidney disease incidence and progression, heart failure, and death were evaluated. ANALYTICAL APPROACH: Cox proportional hazard models. RESULTS: Among 1,474 participants with plasma biomarker measurements, 19% had kidney disease progression, 14% had later heart failure, and 21% died during a median follow-up of 4.4 years. For the kidney outcome, the adjusted HRs (AHRs) per doubling in concentration were 2.9 (95% CI, 2.2-3.9) for sTNFR1 and 1.9 (95% CI, 1.5-2.5) for sTNFR2. AKI during the index hospitalization did not modify the association between biomarkers and kidney events. For heart failure, the AHRs per doubling in concentration were 1.9 (95% CI, 1.4-2.5) for sTNFR1 and 1.5 (95% CI, 1.2-2.0) for sTNFR2. For mortality, the AHRs were 3.3 (95% CI, 2.5-4.3) for sTNFR1 and 2.5 (95% CI, 2.0-3.1) for sTNFR2. The findings in ARID were qualitatively similar in terms of the magnitude of association between biomarkers and outcomes. LIMITATIONS: Different biomarker platforms and AKI definitions; limited generalizability to other ethnic groups. CONCLUSIONS: Plasma sTNFR1 and sTNFR2 measured 3 months after hospital discharge were independently associated with clinical events regardless of AKI status during the index admission. sTNFR1 and sTNFR2 may assist with the risk stratification of patients during follow-up.

Derivation and independent validation of kidneyintelX.dkd: A prognostic test for the assessment of diabetic kidney disease progression.

AIMS: To develop and validate an updated version of KidneyIntelX (kidneyintelX.dkd) to stratify patients for risk of progression of diabetic kidney disease (DKD) stages 1 to 3, to simplify the test for clinical adoption and support an application to the US Food and Drug Administration regulatory pathway. METHODS: We used plasma biomarkers and clinical data from the Penn Medicine Biobank (PMBB) for training, and independent cohorts (BioMe and CANVAS) for validation. The primary outcome was progressive decline in kidney function (PDKF), defined by a ≥40% sustained decline in estimated glomerular filtration rate or end-stage kidney disease within 5 years of follow-up. RESULTS: In 573 PMBB participants with DKD, 15.4% experienced PDKF over a median of 3.7 years. We trained a random forest model using biomarkers and clinical variables. Among 657 BioMe participants and 1197 CANVAS participants, 11.7% and 7.5%, respectively, experienced PDKF. Based on training cut-offs, 57%, 35% and 8% of BioMe participants, and 56%, 38% and 6% of CANVAS participants were classified as having low-, moderate- and high-risk levels, respectively. The cumulative incidence at these risk levels was 5.9%, 21.2% and 66.9% in BioMe and 6.7%, 13.1% and 59.6% in CANVAS. After clinical risk factor adjustment, the adjusted hazard ratios were 7.7 (95% confidence interval [CI] 3.0-19.6) and 3.7 (95% CI 2.0-6.8) in BioMe, and 5.4 (95% CI 2.5-11.9) and 2.3 (95% CI 1.4-3.9) in CANVAS, for high- versus low-risk and moderate- versus low-risk levels, respectively. CONCLUSIONS: Using two independent cohorts and a clinical trial population, we validated an updated KidneyIntelX test (named kidneyintelX.dkd), which significantly enhanced risk stratification in patients with DKD for PDKF, independently from known risk factors for progression.

Systematic Review and Meta-Analysis of Plasma and Urine Biomarkers for CKD Outcomes.

BACKGROUND: Sensitive and specific biomarkers are needed to provide better biologic insight into the risk of incident and progressive CKD. However, studies have been limited by sample size and design heterogeneity. METHODS: In this assessment of the prognostic value of preclinical plasma and urine biomarkers for CKD outcomes, we searched Embase (Ovid), MEDLINE ALL (Ovid), and Scopus up to November 30, 2020, for studies exploring the association between baseline kidney biomarkers and CKD outcomes (incident CKD, CKD progression, or incident ESKD). We used random-effects meta-analysis. RESULTS: After screening 26,456 abstracts and 352 full-text articles, we included 129 studies in the meta-analysis for the most frequently studied plasma biomarkers (TNFR1, FGF23, TNFR2, KIM-1, suPAR, and others) and urine biomarkers (KIM-1, NGAL, and others). For the most frequently studied plasma biomarkers, pooled RRs for CKD outcomes were 2.17 (95% confidence interval [95% CI], 1.91 to 2.47) for TNFR1 (31 studies); 1.21 (95% CI, 1.15 to 1.28) for FGF-23 (30 studies); 2.07 (95% CI, 1.82 to 2.34) for TNFR2 (23 studies); 1.51 (95% CI, 1.38 to 1.66) for KIM-1 (18 studies); and 1.42 (95% CI, 1.30 to 1.55) for suPAR (12 studies). For the most frequently studied urine biomarkers, pooled RRs were 1.10 (95% CI, 1.05 to 1.16) for KIM-1 (19 studies) and 1.12 (95% CI, 1.06 to 1.19) for NGAL (19 studies). CONCLUSIONS: Studies of preclinical biomarkers for CKD outcomes have considerable heterogeneity across study cohorts and designs, limiting comparisons of prognostic performance across studies. Plasma TNFR1, FGF23, TNFR2, KIM-1, and suPAR were among the most frequently investigated in the setting of CKD outcomes.

Longitudinal TNFR1 and TNFR2 and Kidney Outcomes: Results from AASK and VA NEPHRON-D.

BACKGROUND: Higher baseline levels of soluble TNF receptors (TNFR1 and TNFR2) have been associated with progressive CKD. Whether longitudinal changes in these biomarkers of inflammation are also associated with worse kidney outcomes has been less studied. METHODS: We evaluated associations of longitudinal changes in TNFR1 and TNFR2 with ESKD in the African American Study of Kidney Disease and Hypertension (AASK; 38% female; 0% diabetes) and kidney function decline (first occurrence of ≥30 ml/min per 1.73 m2 or ≥50% eGFR decline if randomization eGFR ≥60 or <60 ml/min per 1.73 m2, respectively; ESKD) in the Veterans Affairs Nephropathy in Diabetes trial (VA NEPHRON-D; 99% male; 100% diabetes) using Cox models. Biomarkers were measured from samples collected at 0-, 12-, and 24-month visits for AASK (serum) and 0- and 12-month visits for VA NEPHRON-D (plasma). Biomarker slopes (AASK) were estimated using linear mixed-effects models. Covariates included sociodemographic/clinical factors, baseline biomarker level, and kidney function. RESULTS: There were 129 ESKD events over a median of 7.0 years in AASK (n=418) and 118 kidney function decline events over a median of 1.5 years in VA NEPHRON-D (n=754). In AASK, each 1 SD increase in TNFR1 and TNFR2 slope was associated with 2.98- and 1.87-fold higher risks of ESKD, respectively. In VA NEPHRON-D, each 1 SD increase in TNFR1 and TNFR2 was associated with 3.20- and 1.43-fold higher risks of kidney function decline, respectively. CONCLUSIONS: Among individuals with and without diabetes, longitudinal increases in TNFR1 and TNFR2 were each associated with progressive CKD, independent of initial biomarker level and kidney function.

Angiopoietins as Prognostic Markers for Future Kidney Disease and Heart Failure Events after Acute Kidney Injury.

BACKGROUND: The mechanisms underlying long-term sequelae after AKI remain unclear. Vessel instability, an early response to endothelial injury, may reflect a shared mechanism and early trigger for CKD and heart failure. METHODS: To investigate whether plasma angiopoietins, markers of vessel homeostasis, are associated with CKD progression and heart failure admissions after hospitalization in patients with and without AKI, we conducted a prospective cohort study to analyze the balance between angiopoietin-1 (Angpt-1), which maintains vessel stability, and angiopoietin-2 (Angpt-2), which increases vessel destabilization. Three months after discharge, we evaluated the associations between angiopoietins and development of the primary outcomes of CKD progression and heart failure and the secondary outcome of all-cause mortality 3 months after discharge or later. RESULTS: Median age for the 1503 participants was 65.8 years; 746 (50%) had AKI. Compared with the lowest quartile, the highest quartile of the Angpt-1:Angpt-2 ratio was associated with 72% lower risk of CKD progression (adjusted hazard ratio [aHR], 0.28; 95% confidence interval [CI], 0.15 to 0.51), 94% lower risk of heart failure (aHR, 0.06; 95% CI, 0.02 to 0.15), and 82% lower risk of mortality (aHR, 0.18; 95% CI, 0.09 to 0.35) for those with AKI. Among those without AKI, the highest quartile of Angpt-1:Angpt-2 ratio was associated with 71% lower risk of heart failure (aHR, 0.29; 95% CI, 0.12 to 0.69) and 68% less mortality (aHR, 0.32; 95% CI, 0.15 to 0.68). There were no associations with CKD progression. CONCLUSIONS: A higher Angpt-1:Angpt-2 ratio was strongly associated with less CKD progression, heart failure, and mortality in the setting of AKI.

Prognostic Significance of Urinary Biomarkers in Patients Hospitalized With COVID-19.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) is common in patients with coronavirus disease 2019 (COVID-19) and associated with poor outcomes. Urinary biomarkers have been associated with adverse kidney outcomes in other settings and may provide additional prognostic information in patients with COVID-19. We investigated the association between urinary biomarkers and adverse kidney outcomes among patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Patients hospitalized with COVID-19 (n=153) at 2 academic medical centers between April and June 2020. EXPOSURE: 19 urinary biomarkers of injury, inflammation, and repair. OUTCOME: Composite of KDIGO (Kidney Disease: Improving Global Outcomes) stage 3 AKI, requirement for dialysis, or death within 60 days of hospital admission. We also compared various kidney biomarker levels in the setting of COVID-19 versus other common AKI settings. ANALYTICAL APPROACH: Time-varying Cox proportional hazards regression to associate biomarker level with composite outcome. RESULTS: Out of 153 patients, 24 (15.7%) experienced the primary outcome. Twofold higher levels of neutrophil gelatinase-associated lipocalin (NGAL) (HR, 1.34 [95% CI, 1.14-1.57]), monocyte chemoattractant protein (MCP-1) (HR, 1.42 [95% CI, 1.09-1.84]), and kidney injury molecule 1 (KIM-1) (HR, 2.03 [95% CI, 1.38-2.99]) were associated with highest risk of sustaining primary composite outcome. Higher epidermal growth factor (EGF) levels were associated with a lower risk of the primary outcome (HR, 0.61 [95% CI, 0.47-0.79]). Individual biomarkers provided moderate discrimination and biomarker combinations improved discrimination for the primary outcome. The degree of kidney injury by biomarker level in COVID-19 was comparable to other settings of clinical AKI. There was evidence of subclinical AKI in COVID-19 patients based on elevated injury biomarker level in patients without clinical AKI defined by serum creatinine. LIMITATIONS: Small sample size with low number of composite outcome events. CONCLUSIONS: Urinary biomarkers are associated with adverse kidney outcomes in patients hospitalized with COVID-19 and may provide valuable information to monitor kidney disease progression and recovery.

Initiation of the SGLT2 inhibitor canagliflozin to prevent kidney and heart failure outcomes guided by HbA1c, albuminuria, and predicted risk of kidney failure.

BACKGROUND: Sodium glucose co-transporter-2 (SGLT2) inhibitors reduce the risk of kidney and heart failure events independent of glycemic effects. We assessed whether initiation of the SGLT2 inhibitor canagliflozin guided by multivariable predicted risk based on clinical characteristics and novel biomarkers is more efficient to prevent clinical outcomes compared to a strategy guided by HbA1c or urinary-albumin-creatinine ratio (UACR) alone. METHODS: We performed a post-hoc analysis of the CANVAS trial including 3713 patients with available biomarker measurements. We compared the number of composite kidney (defined as a sustained 40% decline in eGFR, chronic dialysis, kidney transplantation, or kidney death) and composite heart failure outcomes (defined as heart failure hospitalization or cardiovascular (CV) death) prevented per 1000 patients treated for 5 years when canagliflozin was initiated in patients according to HbA1c ≥ 7.5%, UACR, or multivariable risk models consisting of: (1) clinical characteristics, or (2) clinical characteristics and novel biomarkers. Differences in the rates of events prevented between strategies were tested by Chi2-statistic. RESULTS: After a median follow-up of 6.1 years, 144 kidney events were recorded. The final clinical model included age, previous history of CV disease, systolic blood pressure, UACR, hemoglobin, body weight, albumin, estimated glomerular filtration rate, and randomized treatment assignment. The combined biomarkers model included all clinical characteristics, tumor necrosis factor receptor-1, kidney injury molecule-1, matrix metallopeptidase-7 and interleukin-6. Treating all patients with HbA1c ≥ 7.5% (n = 2809) would prevent 33.0 (95% CI 18.8 to 43.3 ) kidney events at a rate of 9.6 (95% CI 5.5 to 12.6) events prevented per 1000 patients treated for 5 years. The corresponding rates were 5.8 (95% CI 3.4 to 7.9), 16.6 (95% CI 9.5 to 22.0) (P < 0.001 versus HbA1c or UACR approach), and 17.5 (95% CI 10.0 to 23.0) (P < 0.001 versus HbA1c or UACR approach; P = 0.54 versus clinical model). Findings were similar for the heart failure outcome. CONCLUSION: Initiation of canagliflozin based on an estimated risk-based approach prevented more kidney and heart failure outcomes compared to a strategy based on HbA1c or UACR alone. There was no apparent gain from adding novel biomarkers to the clinical risk model. These findings support the use of risk-based assessment using clinical markers to guide initiation of SGLT2 inhibitors in patients with type 2 diabetes.

Prevalence and Outcomes Associated with Hyperuricemia in Hospitalized Patients with COVID-19.

INTRODUCTION: Coronavirus 2019 (COVID-19) can increase catabolism and result in hyperuricemia. Uric acid (UA) potentially causes kidney damage by alteration of renal autoregulation, inhibition of endothelial cell proliferation, cell apoptosis, activation of the pro-inflammatory cascade, and crystal deposition. Hyperuricemia in patients with COVID-19 may contribute to acute kidney injury (AKI) and poor outcomes. METHODS: We included 834 patients with COVID-19 who were >18 years old and hospitalized for >24 h in the Mount Sinai Health System and had at least 1 measurement of serum UA. We examined the association between the first serum UA level and development of acute kidney injury (AKI, defined by KDIGO criteria), major adverse kidney events (MAKE, defined by a composite of all-cause in-hospital mortality or dialysis or 100% increase in serum creatinine from baseline), as well as markers of inflammation and cardiac injury. RESULTS: Among the 834 patients, the median age was 66 years, 42% were women, and the median first serum UA was 5.9 mg/dL (interquartile range 4.5-8.8). Overall, 60% experienced AKI, 52% experienced MAKE, and 32% died during hospitalization. After adjusting for demographics, comorbidities, and laboratory values, a doubling in serum UA was associated with increased AKI (odds ratio [OR] 2.8, 95% confidence interval [CI] 1.9-4.1), MAKE (OR 2.5, 95% CI 1.7-3.5), and in-hospital mortality (OR 1.7, 95% CI 1.3-2.3). Higher serum UA levels were independently associated with a higher level of procalcitonin (ß, 0.6; SE 0.2) and troponin I (ß, 1.2; SE 0.2) but were not associated with serum ferritin, C-reactive protein, and interleukin-6. CONCLUSION: In patients admitted to the hospital for COVID-19, higher serum UA levels were independently associated with AKI, MAKE, and in-hospital mortality in a dose-dependent manner. In addition, hyperuricemia was associated with higher procalcitonin and troponin I levels.

Novel Renal Autologous Cell Therapy for Type 2 Diabetes Mellitus Chronic Diabetic Kidney Disease: Clinical Trial Design.

BACKGROUND: Cell therapies explore unmet clinical needs of patients with chronic kidney disease with the potential to alter the pathway toward end-stage kidney disease. We describe the design and baseline patient characteristics of a phase II multicenter clinical trial utilizing the novel renal autologous cell therapy (REACT), by direct kidney parenchymal injection via the percutaneous approach in adults with type 2 diabetic kidney disease (T2DKD), to delay or potentially avoid renal replacement therapy. DESIGN: The study conducted a prospective, multicenter, randomized control, open-label, phase II clinical trial between an active treatment group (ATG) receiving REACT from the beginning of the trial and a contemporaneous deferred treatment group (DTG) receiving standard of care for 12 months before crossing over to receive REACT. OBJECTIVES: The objective of this study was to establish the safety and efficacy of 2 REACT injections with computed tomography guidance, into the renal cortex of patients with T2DKD administered 6 months apart, and to compare the longitudinal change in renal function between the ATG and the DTG. SETTING: This was a multicenter study conducted in major US hospitals. PATIENTS: We enrolled eighty-three adult patients with T2DKD, who have estimated glomerular filtration rates (eGFRs) between 20 and 50 mL/min/1.73 m2. METHODS: All patients undergo an image-guided percutaneous kidney biopsy to obtain epithelial phenotype selective renal cells isolated from the kidney tissue that is then expanded ex vivo over 4-6 weeks, resulting in the REACT biologic product. Patients are randomized 1:1 into the ATG or the DTG. Primary efficacy endpoints for both study groups include eGFR measurements at baseline and at 3-month intervals, through 24 months after the last REACT injection. Safety analyses include biopsy-related complications, REACT injection, and cellular-related adverse events. The study utilizes Good Clinical and Manufacturing Practices and a Data and Safety Monitoring Board. The sample size confers a statistical power of 80% to detect an eGFR change in the ATG compared to the DTG at 24 months with an α = 0.05. LIMITATIONS: Blinding cannot occur due to the intent to treat procedure, biopsy in both groups, and open trial design. CONCLUSION: This multicenter phase II randomized clinical trial is designed to determine the efficacy and safety of REACT in improving or stabilizing renal function among patients with T2DKD stages 3a-4.

Clinical Utility of KidneyIntelX in Early Stages of Diabetic Kidney Disease in the CANVAS Trial.

INTRODUCTION: KidneyIntelX is a composite risk score, incorporating biomarkers and clinical variables for predicting progression of diabetic kidney disease (DKD). The utility of this score in the context of sodium glucose co-transporter 2 inhibitors and how changes in the risk score associate with future kidney outcomes are unknown. METHODS: We measured soluble tumor necrosis factor receptor (TNFR)-1, soluble TNFR-2, and kidney injury molecule 1 on banked samples from CANagliflozin cardioVascular Assessment Study (CANVAS) trial participants with baseline DKD (estimated glomerular filtration rate [eGFR] 30-59 mL/min/1.73 m2 or urine albumin-to-creatinine ratio [UACR] ≥30 mg/g) and generated KidneyIntelX risk scores at baseline and years 1, 3, and 6. We assessed the association of baseline and changes in KidneyIntelX with subsequent DKD progression (composite outcome of an eGFR decline of ≥5 mL/min/year [using the 6-week eGFR as the baseline in the canagliflozin group], ≥40% sustained decline in the eGFR, or kidney failure). RESULTS: We included 1,325 CANVAS participants with concurrent DKD and available baseline plasma samples (mean eGFR 65 mL/min/1.73 m2 and median UACR 56 mg/g). During a mean follow-up of 5.6 years, 131 participants (9.9%) experienced the composite kidney outcome. Using risk cutoffs from prior validation studies, KidneyIntelX stratified patients to low- (42%), intermediate- (44%), and high-risk (15%) strata with cumulative incidence for the outcome of 3%, 11%, and 26% (risk ratio 8.4; 95% confidence interval [CI]: 5.0, 14.2) for the high-risk versus low-risk groups. The differences in eGFR slopes for canagliflozin versus placebo were 0.66, 1.52, and 2.16 mL/min/1.73 m2 in low, intermediate, and high KidneyIntelX risk strata, respectively. KidneyIntelX risk scores declined by 5.4% (95% CI: -6.9, -3.9) in the canagliflozin arm at year 1 versus an increase of 6.3% (95% CI: 3.8, 8.7) in the placebo arm (p < 0.001). Changes in the KidneyIntelX score at year 1 were associated with future risk of the composite outcome (odds ratio per 10 unit decrease 0.80; 95% CI: 0.77, 0.83; p < 0.001) after accounting for the treatment arm, without evidence of effect modification by the baseline KidneyIntelX risk stratum or by the treatment arm. CONCLUSIONS: KidneyIntelX successfully risk-stratified a large multinational external cohort for progression of DKD, and greater numerical differences in the eGFR slope for canagliflozin versus placebo were observed in those with higher baseline KidneyIntelX scores. Canagliflozin treatment reduced KidneyIntelX risk scores over time and changes in the KidneyIntelX score from baseline to 1 year associated with future risk of DKD progression, independent of the baseline risk score and treatment arm.

Urinary Biomarkers of Tubular Health and Risk for Kidney Function Decline or Mortality in Diabetes.

INTRODUCTION: Diabetes is a leading cause of end-stage kidney disease (ESKD). Biomarkers of tubular health may prognosticate chronic kidney disease (CKD) progression beyond estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR). METHODS: We examined associations of five urinary biomarkers of tubular injury and repair (NGAL, KIM-1, IL-18, MCP-1, YKL-40) with kidney function decline (first occurrence of a decrease in eGFR ≥30 mL/min/1.73 m2 if randomization eGFR ≥60 or ≥50% if randomization eGFR <60; ESKD) and all-cause mortality among 1,135 VA NEPHRON-D trial participants with baseline UACR ≥300 mg/g and available urine samples. Covariates included age, sex, race, BMI, systolic BP, HbA1c, treatment arm, eGFR, and UACR. In a subset of participants with 12-month samples (n = 712), we evaluated associations of KIM-1, MCP-1, and YKL-40 change (from baseline to 12 months) with eGFR decline (from 12 months onward). RESULTS: At baseline, mean age was 65 years, mean eGFR was 56 mL/min/1.73 m2, and median UACR was 840 mg/g. Over a median of 2.2 years, 13% experienced kidney function decline and 9% died. In fully adjusted models, the highest versus lowest quartiles of MCP-1 and YKL-40 were associated with 2.18- and 1.76-fold higher risks of kidney function decline, respectively. One-year changes in KIM-1, MCP-1, and YKL-40 were not associated with subsequent eGFR decline. Higher baseline levels of NGAL, IL-18, MCP-1, and YKL-40 levels (per 2-fold higher) were independently associated with 10-40% higher risk of mortality. CONCLUSION: Among Veterans with diabetes and CKD, urinary biomarkers of tubular health were associated with kidney function decline and mortality.

High Oxalate Concentrations Correlate with Increased Risk for Sudden Cardiac Death in Dialysis Patients.

BACKGROUND: The clinical significance of accumulating toxic terminal metabolites such as oxalate in patients with kidney failure is not well understood. METHODS: To evaluate serum oxalate concentrations and risk of all-cause mortality and cardiovascular events in a cohort of patients with kidney failure requiring chronic dialysis, we performed a post-hoc analysis of the randomized German Diabetes Dialysis (4D) Study; this study included 1255 European patients on hemodialysis with diabetes followed-up for a median of 4 years. The results obtained via Cox proportional hazards models were confirmed by competing risk regression and restricted cubic spline modeling in the 4D Study cohort and validated in a separate cohort of 104 US patients on dialysis after a median follow-up of 2.5 years. RESULTS: A total of 1108 patients had baseline oxalate measurements, with a median oxalate concentration of 42.4 µM. During follow-up, 548 patients died, including 139 (25.4%) from sudden cardiac death. A total of 413 patients reached the primary composite cardiovascular end point (cardiac death, nonfatal myocardial infarction, and fatal or nonfatal stroke). Patients in the highest oxalate quartile (≥59.7 µM) had a 40% increased risk for cardiovascular events (adjusted hazard ratio [aHR], 1.40; 95% confidence interval [95% CI], 1.08 to 1.81) and a 62% increased risk of sudden cardiac death (aHR, 1.62; 95% CI, 1.03 to 2.56), compared with those in the lowest quartile (≤29.6 µM). The associations remained when accounting for competing risks and with oxalate as a continuous variable. CONCLUSIONS: Elevated serum oxalate is a novel risk factor for cardiovascular events and sudden cardiac death in patients on dialysis. Further studies are warranted to test whether oxalate-lowering strategies improve cardiovascular mortality in patients on dialysis.

AKI in Hospitalized Patients with COVID-19.

BACKGROUND: Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associated with worse outcomes. However, AKI among hospitalized patients with COVID-19 in the United States is not well described. METHODS: This retrospective, observational study involved a review of data from electronic health records of patients aged ≥18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality. RESULTS: Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patients with AKI required dialysis. The proportions with stages 1, 2, or 3 AKI were 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up. CONCLUSIONS: AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.

AKI Treated with Renal Replacement Therapy in Critically Ill Patients with COVID-19.

BACKGROUND: AKI is a common sequela of coronavirus disease 2019 (COVID-19). However, few studies have focused on AKI treated with RRT (AKI-RRT). METHODS: We conducted a multicenter cohort study of 3099 critically ill adults with COVID-19 admitted to intensive care units (ICUs) at 67 hospitals across the United States. We used multivariable logistic regression to identify patient-and hospital-level risk factors for AKI-RRT and to examine risk factors for 28-day mortality among such patients. RESULTS: A total of 637 of 3099 patients (20.6%) developed AKI-RRT within 14 days of ICU admission, 350 of whom (54.9%) died within 28 days of ICU admission. Patient-level risk factors for AKI-RRT included CKD, men, non-White race, hypertension, diabetes mellitus, higher body mass index, higher d-dimer, and greater severity of hypoxemia on ICU admission. Predictors of 28-day mortality in patients with AKI-RRT were older age, severe oliguria, and admission to a hospital with fewer ICU beds or one with greater regional density of COVID-19. At the end of a median follow-up of 17 days (range, 1-123 days), 403 of the 637 patients (63.3%) with AKI-RRT had died, 216 (33.9%) were discharged, and 18 (2.8%) remained hospitalized. Of the 216 patients discharged, 73 (33.8%) remained RRT dependent at discharge, and 39 (18.1%) remained RRT dependent 60 days after ICU admission. CONCLUSIONS: AKI-RRT is common among critically ill patients with COVID-19 and is associated with a hospital mortality rate of >60%. Among those who survive to discharge, one in three still depends on RRT at discharge, and one in six remains RRT dependent 60 days after ICU admission.

Effects of the SGLT2 inhibitor canagliflozin on plasma biomarkers TNFR-1, TNFR-2 and KIM-1 in the CANVAS trial.

AIMS/HYPOTHESIS: Higher plasma concentrations of tumour necrosis factor receptor (TNFR)-1, TNFR-2 and kidney injury molecule-1 (KIM-1) have been found to be associated with higher risk of kidney failure in individuals with type 2 diabetes in previous studies. Whether drugs can reduce these biomarkers is not well established. We measured these biomarkers in samples of the CANVAS study and examined the effect of the sodium-glucose cotransporter 2 inhibitor canagliflozin on these biomarkers and assessed whether the early change in these biomarkers predict cardiovascular and kidney outcomes in individuals with type 2 diabetes in the CANagliflozin cardioVascular Assessment Study (CANVAS). METHODS: Biomarkers were measured with immunoassays (proprietary multiplex assay performed by RenalytixAI, New York, NY, USA) at baseline and years 1, 3 and 6. Mixed-effects models for repeated measures assessed the effect of canagliflozin vs placebo on the biomarkers. Associations of baseline levels and the early change (baseline to year 1) for each biomarker with the kidney outcome were assessed using multivariable-adjusted Cox regression. RESULTS: In total, 3523/4330 (81.4%) of the CANVAS participants had available samples at baseline. Each doubling in baseline TNFR-1, TNFR-2 and KIM-1 was associated with a higher risk of kidney outcomes, with corresponding HRs of 3.7 (95% CI 2.3, 6.1; p < 0.01), 2.7 (95% CI 2.0, 3.6; p < 0.01) and 1.5 (95% CI 1.2, 1.8; p < 0.01), respectively. Canagliflozin reduced the level of the plasma biomarkers with differences in TNFR-1, TNFR-2 and KIM-1 between canagliflozin and placebo during follow-up of 2.8% (95% CI 3.4%, 1.3%; p < 0.01), 1.9% (95% CI 3.5%, 0.2%; p = 0.03) and 26.7% (95% CI 30.7%, 22.7%; p < 0.01), respectively. Within the canagliflozin treatment group, each 10% reduction in TNFR-1 and TNFR-2 at year 1 was associated with a lower risk of the kidney outcome (HR 0.8 [95% CI 0.7, 1.0; p = 0.02] and 0.9 [95% CI 0.9, 1.0; p < 0.01] respectively), independent of other patient characteristics. The baseline and 1 year change in biomarkers did not associate with cardiovascular or heart failure outcomes. CONCLUSIONS/INTERPRETATION: Canagliflozin decreased KIM-1 and modestly reduced TNFR-1 and TNFR-2 compared with placebo in individuals with type 2 diabetes in CANVAS. Early decreases in TNFR-1 and TNFR-2 during canagliflozin treatment were independently associated with a lower risk of kidney disease progression, suggesting that TNFR-1 and TNFR-2 have the potential to be pharmacodynamic markers of response to canagliflozin.

Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict progression of diabetic kidney disease.

AIM: Predicting progression in diabetic kidney disease (DKD) is critical to improving outcomes. We sought to develop/validate a machine-learned, prognostic risk score (KidneyIntelX™) combining electronic health records (EHR) and biomarkers. METHODS: This is an observational cohort study of patients with prevalent DKD/banked plasma from two EHR-linked biobanks. A random forest model was trained, and performance (AUC, positive and negative predictive values [PPV/NPV], and net reclassification index [NRI]) was compared with that of a clinical model and Kidney Disease: Improving Global Outcomes (KDIGO) categories for predicting a composite outcome of eGFR decline of ≥5 ml/min per year, ≥40% sustained decline, or kidney failure within 5 years. RESULTS: In 1146 patients, the median age was 63 years, 51% were female, the baseline eGFR was 54 ml min-1 [1.73 m]-2, the urine albumin to creatinine ratio (uACR) was 6.9 mg/mmol, follow-up was 4.3 years and 21% had the composite endpoint. On cross-validation in derivation (n = 686), KidneyIntelX had an AUC of 0.77 (95% CI 0.74, 0.79). In validation (n = 460), the AUC was 0.77 (95% CI 0.76, 0.79). By comparison, the AUC for the clinical model was 0.62 (95% CI 0.61, 0.63) in derivation and 0.61 (95% CI 0.60, 0.63) in validation. Using derivation cut-offs, KidneyIntelX stratified 46%, 37% and 17% of the validation cohort into low-, intermediate- and high-risk groups for the composite kidney endpoint, respectively. The PPV for progressive decline in kidney function in the high-risk group was 61% for KidneyIntelX vs 40% for the highest risk strata by KDIGO categorisation (p < 0.001). Only 10% of those scored as low risk by KidneyIntelX experienced progression (i.e., NPV of 90%). The NRIevent for the high-risk group was 41% (p < 0.05). CONCLUSIONS: KidneyIntelX improved prediction of kidney outcomes over KDIGO and clinical models in individuals with early stages of DKD.